Thermal Radiation Measurement and Development of Tunable Plasmonic Thermal Emitter Using Strain-induced Buckling in Metallic Layers

An infrared radiometry setup has been developed based on a commercially available FTIR spectrometer for measuring mid-infrared thermal radiation. The setup was calibrated with a lab-built blackbody source. The setup was tested with a grating structure with 4-micron periodicity. Periodic microstructures using nickel and gold are fabricated on elastomeric substrates by use of strain-induced buckling of the nickel layer. The intrinsically low emissivity of gold in the mid-infrared regime is selectively enhanced by the surface plasmonic resonance at three different mid-infrared wavelengths, 4.5 µm, 6.3 µm, and 9.4 µm. As the thermal emission enhancement effect exists only for the polarization perpendicular to the orientation of the microstructures, substantially polarized thermal emission with an extinction ratio of close to 3 is demonstrated. Moreover, the elastically deformed plasmonic thermal emitters demonstrate strain-dependent emission peaks, which can be applied for future mechano-thermal sensing and dynamic thermal signature modulation

Time Series Synthesis via Multi-scale Patch-based Generation of Wavelet Scalogram

A framework is proposed for the unconditional generation of synthetic time series based on learning from a single sample in low-data regime case. The framework aims at capturing the distribution of patches in wavelet scalogram of time series using single image generative models and producing realistic wavelet coefficients for the generation of synthetic time series. It is demonstrated that the framework is effective with respect to fidelity and diversity for time series with insignificant to no trends. Also, the performance is more promising for generating samples with the same duration (reshuffling) rather than longer ones (retargeting).Comment: 8 pages, 3 figures, 2 table

Earthquake response of monopiles and caissons for Offshore Wind Turbines founded in liquefiable soil

Abstract Monopile has been the most widespread foundation type for Offshore Wind Turbines (OWTs) in shallow waters. Caisson (skirted) foundations have also been evaluated in some projects as an economical alternative. While the main concern in design of offshore foundations has been the environmental loads, the recent growth in construction of OWTs in seismic regions with the possibility of soil liquefaction has necessitated evaluation of the impact of earthquake and liquefaction from strong shakings on these structures. Several studies have reported the consequences of soil liquefaction for buildings and onshore structures; However, the effects of liquefaction on offshore foundations have not been sufficiently studied. This paper investigates the use of advanced liquefaction modeling in assessment of the response of monopiles and caissons for offshore wind turbines. The software FLAC3D and the SANISAND constitutive model are used to conduct the nonlinear dynamic analyses for OWTs. Excess pore water pressure during earthquake shaking and earthquake-induced displacements are computed at various points in the soil medium around the considered monopile and caisson foundations. The analyses reveal that SANISAND model is capable of simulating the pore pressure generation in the free-field as observed in a recent centrifuge test. The numerical results also indicate that both monopile and caissons in liquefiable soil deposits experience considerable rotations under the combined action of wind loads and earthquake shaking when liquefaction occurs

Numerical modeling of liquefaction and its impact on anchor piles for floating offshore structures

Anchor piles and suction anchors have been used for anchoring different types of offshore structure in the past four decades. The recent growing interest and demand for wind energy has motivated the industry to evaluate the use of Offshore Wind Turbines (OWT) in deep waters for which floating wind turbine is a good alternative to bottom-fixed solutions particularly in seismic regions with possibility of soil liquefaction. Extensive research has been carried out to assess the consequences of soil liquefaction for buildings and onshore structures; however, this phenomenon has not been sufficiently studied for offshore foundations. This paper aims at investigating the use of advanced liquefaction modeling in assessment of the performance of anchor piles for offshore facilities and in particular floating offshore wind turbines. The software FLAC3D is used to carry out the nonlinear dynamic analyses using SANISAND constitutive model for saturated sand. The analyses indicate that SANISAND model is capable of correctly simulating the excess pore water pressure in the free-field as observed in centrifuge tests. Pore pressure build-up due to earthquake shaking together with earthquake-induced displacements are computed at various points in the soil medium containing an anchor pile in different scenarios. The numerical results indicate that anchor piles may experience permanent lateral displacements and tilt due to the combined action of static mooring load and earthquake shaking leading to soil liquefaction. (C) 2019 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Seismic response of subsea structures on caissons and mudmats due to liquefaction

Abstract This paper presents a numerical study to investigate the seismic behavior of mudmat and caisson foundations supporting subsea structures, such as manifolds, in liquefiable sand. In seismic areas, substantial earthquake loads can be imparted to subsea structures during ground shaking, threatening their stability. In particular, soil liquefaction in sandy soil arising from strong ground motions could significantly influence the performance of subsea structures founded on liquefiable sand. The results of this study can provide a better understanding of the response of subsea manifolds in liquefiable soil during and after the earthquake. Three-dimensional, non-linear, dynamic analyses are performed using a finite difference scheme, and the ability of the model to reproduce the site response of a saturated sand deposit is assessed using the results of available centrifuge data. This study includes six computational models representing manifolds with different sizes and weights supported by caissons and mudmats in shallow and deep liquefiable sand subjected to moderate and strong earthquake shakings. The response is evaluated in terms of excess pore water pressure generated in the soil medium and displacements of the subsea foundation during and after the shaking. The results show that manifolds may experience considerable movement during liquefaction and post-liquefaction settlements. In addition, depending on the characteristics of the seismic motion and structural system, the manifold could also experience large tilting

Sequence Generation via Subsequence Similarity: Theory and Application to UAV Identification

The ability to generate synthetic sequences is crucial for a wide range of applications, and recent advances in deep learning architectures and generative frameworks have greatly facilitated this process. Particularly, unconditional one-shot generative models constitute an attractive line of research that focuses on capturing the internal information of a single image, video, etc. to generate samples with similar contents. Since many of those one-shot models are shifting toward efficient non-deep and non-adversarial approaches, we examine the versatility of a one-shot generative model for augmenting whole datasets. In this work, we focus on how similarity at the subsequence level affects similarity at the sequence level, and derive bounds on the optimal transport of real and generated sequences based on that of corresponding subsequences. We use a one-shot generative model to sample from the vicinity of individual sequences and generate subsequence-similar ones and demonstrate the improvement of this approach by applying it to the problem of Unmanned Aerial Vehicle (UAV) identification using limited radio-frequency (RF) signals. In the context of UAV identification, RF fingerprinting is an effective method for distinguishing legitimate devices from malicious ones, but heterogenous environments and channel impairments can impose data scarcity and affect the performance of classification models. By using subsequence similarity to augment sequences of RF data with a low ratio (5\%-20\%) of training dataset, we achieve significant improvements in performance metrics such as accuracy, precision, recall, and F1 score.Comment: 12 pages, 5 figures, 2 table

Seismic response of subsea structures on caissons and mudmats due to liquefaction

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